Name
Abstract | ||
|---|---|---|
Mathematics and computing students learn new concepts and fortify their expertise by solving problems. The representation of a problem, be it through algebra, diagrams, or code, is key to understanding and solving it. Multiple-representation interactive environments are a promising approach, but the task of choosing an appropriate representation is largely placed on the user. We propose a new method to recommend representations based on correspondences: conceptual links between domains. Correspondences can be used to analyse, identify, and construct analogies even when the analogical target is unknown. This paper explains how correspondences build on probability theory and Gentner’s structure-mapping framework; proposes rules for semi-automated correspondence discovery; and describes how correspondences can explain and construct analogies. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/VL/HCC50065.2020.9127258 | 2020 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) |
Keywords | DocType | ISSN |
analogy,problem-solving,representation | Conference | 1943-6092 |
ISBN | Citations | PageRank |
978-1-7281-6901-9 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aaron Stockdill | 1 | 0 | 1.69 |
| Daniel Raggi | 2 | 0 | 1.69 |
| Mateja Jamnik | 3 | 158 | 30.79 |
| Grecia Garcia Garcia | 4 | 7 | 3.64 |
| Holly E. A. Sutherland | 5 | 0 | 0.34 |
| Peter C.-H. Cheng | 6 | 0 | 0.34 |
| Advait Sarkar | 7 | 22 | 4.64 |